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Factorized solution of generalized stable Sylvester equations using many-core GPU accelerators

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Factorized solution of generalized stable Sylvester equations using many-core GPU accelerators

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Benner, P.; Dufrechou, E.; Ezzatti, P.; Gallardo, R.; Quintana-Ortí, ES. (2021). Factorized solution of generalized stable Sylvester equations using many-core GPU accelerators. The Journal of Supercomputing (Online). 77(9):10152-19164. https://doi.org/10.1007/s11227-021-03658-y

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Título: Factorized solution of generalized stable Sylvester equations using many-core GPU accelerators
Autor: Benner, Peter Dufrechou, Ernesto Ezzatti, Pablo Gallardo, Rodrigo Quintana-Ortí, Enrique S.
Entidad UPV: Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors
Fecha difusión:
Resumen:
[EN] We investigate the factorized solution of generalized stable Sylvester equations such as those arising in model reduction, image restoration, and observer design. Our algorithms, based on the matrix sign function, ...[+]
Palabras clave: Sylvester equation , Matrix sign function , Newton iteration , GPUs
Derechos de uso: Reserva de todos los derechos
Fuente:
The Journal of Supercomputing (Online). (eissn: 1573-0484 )
DOI: 10.1007/s11227-021-03658-y
Editorial:
Springer-Verlag
Versión del editor: https://doi.org/10.1007/s11227-021-03658-y
Agradecimientos:
We acknowledge support of the ANII - MPG Independent Research Group: "Efficient Hetergenous Computing" at UdelaR, a partner group of the Max Planck Institute in Magdeburg.
Tipo: Artículo

References

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